Health survey on anxiety, depression, and stress in Afghanistan: A large-scale cross-sectional survey study

Health survey on anxiety, depression, and stress in Afghanistan: A large-scale cross-sectional survey study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Health survey on anxiety, depression, and stress in Afghanistan: A large-scale cross-sectional survey study Ahmad Neyazi, Abdul Qadim Mohammadi, Nosaibah Razaqi, Bilal Ahmad Rahimi, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4149818/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background: The present cross-sectional survey study examined the mental health of Afghans living under the Taliban government. It examined the underlying factors associated with depression, anxiety, and stress. Methods: Between June 5, 2023 and February 12, 2024, a cross-sectional study was conducted among the Afghan population in three key regions of Afghanistan. Data were collected using a pretested structured questionnaire. Logistic regression models were employed to explore the relationship between socio-demographic characteristics and depression, anxiety, and stress among 2,698 participants. Results: The prevalence of (i) depression was 72.05%, (ii) anxiety was 71.94%, and (iii) stress was 66.49%. Multiple regression analysis indicated that gender (being female), economic status (being poor), residency (living in rural areas), education level (being illiterate), being a cigarette smoker, and having experienced a traumatic event during the past month were significantly associated with depression, anxiety and stress. Conclusion: The mental health crisis in Afghanistan is a complex and urgent issue that requires a comprehensive and compassionate response. The findings of the present study show very high levels of anxiety, depression, and stress, most likely reflecting the profound impact of recent political, social, and economic changes. Notably, a significant majority of participants, particularly females and individuals above 35 years of age, reported severe to extremely severe mental health symptoms. depression anxiety stress Afghanistan Taliban Figures Figure 1 Figure 2 Introduction Afghanistan, located in South Asia, has been a region of significant political and geopolitical importance for decades. The country has experienced a tumultuous history, marked by conflicts, foreign interventions, and political changes [ 1 ]. One of the most significant events in recent Afghan history is the rise of the Taliban and the war that followed, which had profound impacts on the lives of Afghans [ 1 , 2 ]. The Taliban is an extremist Islamist group that emerged in the early 1990s. They gained control of Afghanistan in 1996, imposing a strict interpretation of Islamic law. Following the 9/11 attacks in the United States in 2001, the U.S. and its allies initiated Operation Enduring Freedom to oust the Taliban regime and dismantle Al-Qaeda [ 3 , 4 ]. The war evolved into a protracted conflict, characterized by insurgency, counterinsurgency efforts, and complex alliances with Afghan factions [ 5 ]. After the fall of the Taliban in 2001, efforts were made to rebuild Afghanistan, establish democratic institutions, and promote human rights and gender equality. Despite these efforts, corruption, political instability, and a resurgent Taliban posed ongoing challenges to the nation's development. However, in August 2021, the Taliban regained control of the country as United States and NATO forces withdrew, leading to concerns about the protection of human rights and the Afghan people's future [ 3 , 5 ]. The Afghan conflict has had far-reaching global implications, influencing regional stability, refugee crises, and counterterrorism efforts [ 6 ]. The situation in Afghanistan is highly fluid, and the well-being of its citizens remain a global concern. The complex history of Afghanistan, the rise of the Taliban, and the enduring war have left a deep impact on the lives of Afghans, shaping the country's destiny and its place in the world [ 6 , 7 ]. The mental health of the Afghan people has long been a matter of concern due to decades of conflict and instability in the region. The return of the Taliban to power in Afghanistan in recent years has raised new and urgent questions about the well-being of its citizens [ 8 ]. Afghanistan has been marred by war and violence for generations. The resurgence of the Taliban has the potential to trigger or exacerbate trauma among individuals who have experienced violence, displacement, and loss [ 8 , 9 ]. Post-traumatic stress disorder (PTSD) is a significant concern, given the cumulative effects of prolonged conflict [ 10 ]. The uncertainty associated with Taliban rule, especially concerning women's rights, freedom of expression, and personal freedoms, appears to have generated widespread anxiety and fear among Afghan citizens [ 10 , 11 ]. Living under strict rules and facing harsh consequences for non-compliance can take a significant toll on individuals’ mental well-being. The loss of livelihoods, the breakdown of essential services, and the general sense of hopelessness can lead to high rates of depression among the Afghan population [ 10 , 12 ]. Furthermore, the lack of economic prospects and the absence of a stable environment can contribute to a sense of despair [ 12 ]. Mental health issues are often stigmatized in Afghan society, making it challenging for individuals to seek help or confide in others [ 13 , 14 ]. The fear of being ostracized or labeled as weak can lead to social isolation for those grappling with mental health challenges [ 15 , 16 ]. Also, the country is facing significant hurdles in providing mental health services to the Afghan people. Conflict and instability have strained the healthcare system, making it difficult for individuals to access the support they need. The current situation has likely exacerbated this issue, leaving many without proper care [ 17 , 18 ]. Furthermore, the condition of Afghan women under Taliban rule cannot be underestimated. Gender-based violence, forced marriages, and the fear of losing access to education and employment can lead to severe anxiety, depression, and trauma among women [ 9 , 19 ]. With approximately 90% of the Afghan population experiencing the deleterious effects of poverty [ 20 ], the plight of women and girls has become even more pronounced [ 21 ]. Under the governance of the Taliban, women encounter constraints in various domains, including education, employment, mobility, political involvement, healthcare access, and public visibility [ 21 ]. These circumstances have the potential to exacerbate pre-existing mental health disorders among the populace. Additionally, the advent of COVID-19, coupled with other contributing factors (e.g., poverty), is likely to have adversely affected mental well-being [ 22 ]. The closure of numerous schools and daycare facilities has compelled women to shoulder additional responsibilities, including the care of children and/or elderly family members, often concurrently managing remote work obligations [ 21 ]. This heightened workload has the potential to engender feelings of fatigue, frustration, and burnout, collectively posing a considerable threat to mental health [ 23 ]. Despite the aforementioned research, there has been no prior research examining the levels of depression, anxiety, and stress experienced by Afghans at a national level during the Taliban's governance. Therefore, the present study examined these mental health aspects collectively among Afghans. Additionally, it explored the underlying factors associated with depression, anxiety, and stress. Lastly, the study examined how socio-demographic traits of Afghans under Taliban rule relate to these three mental health indicators. As the study was exploratory, there were no specific hypotheses Methods Participants, study design, and procedure Between June 5, 2023 and February 12, 2024, a cross-sectional study was conducted. The study comprised 2,698 participants (1234 men and 1464 women), ranging in age from 15 to 100 years (mean age = 30.96 years; SD ± 13.70). These participants were recruited from various regions in Afghanistan, namely the southern region (Kandahar, Helmand), western region (Herat, Badghis, Farah, Ghor), and northern region (Mazar-e-Sharif, Samangan) [Figure 1 ]. Data were collected through face-to-face interviews conducted by 15 trained data collectors. Participants were recruited using cluster convenience sampling. A total of 3080 individuals residing in the aforementioned provinces were directly invited to participate in the study by approaching them outdoors in streets where they lived and/or worked. Among these, 2698 individuals volunteered to be interviewed (response rate = 87.6%). To be eligible for the study, individuals had to meet specific criteria. More specifically, they had to be: (i) residents of Afghanistan, (ii) aged at least 15 years, (iii) able to understand either Dari or Pashto languages, and (iv) able to provide either written or verbal informed consent (those aged 15–18 years were also required to have additional consent from their parents). The target sample size was determined using the formula N = Zα2P(1 − P)/d2, with α = 0.05 and Zα = 1.96, and a margin of error (d) of 5% which means the minimum sample size for each cluster (province) was 385. The proportion of women experiencing depression and anxiety was estimated at 80% based on existing Afghan literature [ 23 ]. No recent prevalence estimates exist for males. OpenEpi software (v3.01) was employed to calculate the sample size. Instruments The present study utilized a survey comprising two sections: one focused on socio-demographic information and the other on mental health issues (i.e., assessing depression, anxiety, and stress levels). The socio-demographic section comprised questions relating to age, marital status, residency, education level, economic status, cigarette smoking status, and whether participants had experienced a bad event in the past month (defined as any action or occurrence that occurred within the past month that led the participant to feel down or depressed). The interpretation of what constituted a "bad event" was left to the participants. To assess participants' levels of depression, anxiety, and stress, the Persian version of the 21-item Depression Anxiety Stress Scale (DASS-21) was employed [ 24 ]. The scale is divided into three sub-domains: depression, anxiety, and stress. Responses for all items, such as "I couldn't seem to experience any positive feeling at all" are scored on a scale from 0 ( "Did not apply to me at all" ) to 3 ( "Applied to me very much or most of the time" ). Scores for each sub-domain range from 0 to 21. To obtain the final score for each sub-domain, the score was multiplied by two, resulting in the same scoring as the longer DASS-42. For the depression sub-domain, the standard cut-off scores were applied: 0 to 9 indicated normal levels, 10 to 13 indicated mild depression, 14 to 20 indicated moderate depression, and scores above 20 indicated severe to extremely severe depression symptoms. In the present study, Cronbach’s alpha for the depression subscale was 0.849. Similarly, for the anxiety sub-domain, scores between 0 to 7 are considered normal, 8 to 9 indicate mild anxiety, 10 to 14 indicate moderate anxiety, and scores higher than 14 indicate severe to extremely severe anxiety symptoms. Cronbach’s alpha for anxiety subscale in the present study was 0.836. For the stress sub-domain, scores between 0 to 14 are considered normal, 15 to 18 indicate mild stress, 19 to 25 indicate moderate stress, and scores higher than 25 indicate severe to extremely severe stress symptoms. Cronbach’s alpha for the stress subscale in the present study was 0.874. Analysis The data were entered using Microsoft Excel 2016, while the analysis was conducted using IBM SPSS version 26.0 for Windows. Descriptive statistics comprised means, standard deviations, frequencies, and percentages. Associations between variables were assessed utilizing chi-square tests. To explore the independent socio-demographic factors associated with depression, anxiety, and stress, a multiple regression analysis was employed. Variables with a p -value below 0.05 were considered statistically significant. Results Of the 2698 participants, more than half of participants were female (54.3%), almost two-thirds of the participants were married (63.7%), and two-thirds of the participants were living in urban areas (66.6%). One-eighth of the participants had university level education (14.0%), and more than four-fifths of the participants had low-income economic status (81.0%). One-tenth had ever smoked while nine-tenths of the participants had never smoked (90.2%). Table 1 provides a detailed breakdown of the participants’ characteristics [Table 1 ]. Table 1 Characteristics distribution of the study sample (n = 2698) Characteristic Categories Male Female Total N % N % N % Age group 15–34-years 35–100-years 914 320 47.5 41.3 1010 454 52.5 58.7 1924 774 71.3 28.7 Marital status Single Married Widow/divorced 465 759 10 51.2 44.2 14.1 444 959 61 48.8 55.8 85.9 909 1718 71 33.7 63.7 2.6 Residency Urban Rural 769 465 42.8 51.7 1029 435 57.2 48.3 1798 900 66.6 33.4 Education Illiterate Primary school Secondary school High school University 329 162 242 324 177 35.1 49.7 51.4 55.1 46.9 607 164 229 264 200 64.9 50.3 48.6 44.9 53.1 936 326 471 588 377 34.7 12.1 17.4 21.8 14.0 Economic status High income Middle income Low income 54 196 984 59.3 46.7 45.0 37 224 1203 40.7 53.3 55.0 91 420 2187 3.4 15.6 81.0 Cigarette smoking Never smoked Ex-smoker Current smoker 1021 120 93 41.9 76.4 86.9 1413 37 14 58.1 23.6 13.1 2434 157 107 90.2 5.8 4.0 Bad event occurring in the past month Yes No 650 584 42.5 50.0 880 584 57.5 50.0 1530 1168 56.7 43.3 Total 1234 100.0 1464 100.0 2698 100.0 Among the participants, 510 did not exhibit any signs of depression, anxiety, or stress (18.9%). Conversely, 1557 displayed symptoms of all three conditions (57.7%), with 50.3% reporting severe to extremely severe anxiety, 41.5% reporting severe to extremely severe stress, and 38.73% reporting severe to extremely severe depression. Figure 1 illustrates the intersecting prevalence of depression, anxiety, and stress among the study participants [Figure 1 ]. Almost half of the participants aged 35-100-years had severe to extremely severe depression (49.7%), less than half of the female participants had severe to extremely severe depression (46.4%), and almost two-thirds of the widowed/divorced participants had severe to extremely severe depression (62.0%). More than one-third of the participants living in urban areas had severe to extremely severe depression (36.1%), and one-quarter of participants who had low economic status had no depression (24.4%). There was a significant relationship between presence of severe to extremely severe depression and (i) age group (more prevalent among elder participants), (ii) gender (more prevalent among females), (iii) marital status (more prevalent among married and widow/divorced participants) (iv) residency (more prevalent among residents living in rural areas), (v) education (more prevalent among illiterate participants), (vi) economic status (more prevalent among participants with low-income economic status), and (vii) bad events (more prevalent among participants who experienced a bad event during the past month [Table 2 ]. Table 2 Association of depression with participants socio-demographic characteristics (n = 2698) Characteristic Depression p -value Normal Mild Moderate Severe and extremely severe N (%) N (%) N (%) N (%) Age group 15–34-years 35–100-years 608 (31.6) 146 (18.9) 196 (10.2) 63 (8.1) 460 (23.9) 180 (23.3) 660 (34.3) 385 (49.7) < .001 Gender Male Female 426 (34.5) 328 (22.4) 146 (11.8) 113 (7.7) 297 (24.1) 343 (23.4) 365 (29.6) 680 (46.4) < .001 Marital status Single Married Widow/divorced 321 (35.3) 422 (24.6) 11 (15.5) 105 (11.6) 150 (8.7) 4 (5.6) 226 (24.9) 402 (23.4) 12 (16.9) 257 (28.3) 744 (43.3) 44 (62.0) < .001 Residency Urban Rural 554 (30.8) 200 (22.2) 172 (9.6) 87 (9.7) 423 (23.5) 217 (24.1) 649 (36.1) 396 (44.0) < .001 Education Illiterate Primary school Secondary school High school University 157 (16.8) 77 (23.6) 133 (28.2) 231 (39.3) 156 (41.4) 73 (7.8) 26 (8.0) 57 (12.1) 62 (10.5) 41 (10.9) 200 (21.4) 90 (27.6) 116 (24.6) 143 (24.3) 91 (24.1) 506 (54.1) 133 (40.8) 165 (35.0) 152 (25.9) 89 (23.6) < .001 Economic status High income Middle income Low income 51 (56.0) 170 (40.5) 533 (24.4) 5 (5.5) 48 (11.4) 206(9.4) 18 (19.8) 110 (26.2) 512 (23.4) 17 (18.7) 92 (21.9) 936 (42.8) < .001 Cigarette smoking Never smoked Ex-smoker Current smoker 695 (28.6) 38 (24.2) 21 (19.6) 226 (9.3) 19 (12.1) 14 (13.1) 570 (23.4) 42 (26.8) 28 (26.2) 943 (38.7) 58 (36.9) 44 (41.1) .265 Bad event occurring in the past month Yes No 315 (20.6) 439 (37.6) 146 (9.5) 113 (9.7) 367 (24.0) 273 (23.4) 702 (45.9) 343 (29.4) < .001 Total 754 (27.9) 259 (9.6) 640 (23.7) 1045 (38.7) Almost two-thirds of the participants aged 35-100-years had severe to extremely severe anxiety (66.9%), more than half of the female participants had severe to extremely severe anxiety (56.8%), and almost three-quarters of the widowed/divorced participants had severe to extremely anxiety (71.8%). More than half of the participants living in rural areas had severe to extremely anxiety (57.1%), and one-quarter who had low economic status had no anxiety (24.3%). There was a significant relationship between presence of severe/extremely severe anxiety and (i) age (more prevalent among older participants), (ii) gender (more prevalent among females), (iii) marital status (more prevalent among married and widow/divorced participants) (iv) residency (more prevalent among residents living in rural areas), (v) education (more prevalent among illiterate participants), (vi) economic status (more prevalent among participants with low income economic status), and (vii) bad events (more prevalent among participants who experienced a bad event during the past month [Table 3 ]. Table 3 Association of anxiety with participants socio-demographic characteristics (n = 2698) Characteristic Anxiety p -value Normal Mild Moderate Ex/Severe N (%) N (%) N (%) N (%) Age group 15–34-years 35–100-years 640 (33.3) 117 (15.1) 106 (5.5) 30 (3.9) 337 (17.5) 109 (14.1) 841 (43.7) 518 (66.9) < .001 Gender Male Female 429 (34.8) 328 (22.4) 63 (5.1) 73 (5.0) 215 (17.4) 231 (15.8) 527 (42.7) 832 (56.8) < .001 Marital status Single Married Widow/divorced 352 (38.7) 395 (23.0) 10 (14.1) 53 (5.8) 82 (4.8) 1 (1.4) 160 (17.6) 277 (16.1) 9 (12.7) 344 (37.8) 964 (56.1) 51 (71.8) < .001 Residency Urban Rural 565 (31.4) 192 (21.3) 90 (5.0) 46 (5.1) 298 (16.6) 148 (16.4) 845 (47.0) 514 (57.1) < .001 Education Illiterate Primary school Secondary school High school University 122 (13.0) 77 (23.6) 137 (29.1) 252 (42.9) 169 (44.8) 30 (3.2) 13 (4.0) 42 (8.9) 34 (5.8) 17 (4.5) 145 (15.5) 64 (19.6) 76 (16.1) 93 (15.8) 68 (18.0) 639 (68.3) 172 (52.8) 216 (45.9) 209 (35.5) 123 (32.6) < .001 Economic status High income Middle income Low income 48 (52.7) 178 (42.4) 531 (24.3) 3 (3.3) 30 (7.1) 103 (4.7) 13 (14.3) 73 (17.4) 360 (16.5) 27 (29.7) 139 (33.1) 1193 (54.5) < .001 Cigarette smoking Never smoked Ex-smoker Current smoker 691 (28.4) 42 (26.8) 24 (22.4) 120 (4.9) 9 (5.7) 7 (6.5) 405 (16.6) 24 (15.3) 17 (15.9) 1218 (50.0) 82 (52.2) 59 (55.1) .819 Bad event occurring in the past month Yes No 315 (20.6) 442 (37.8) 83 (5.4) 53 (4.5) 268 (17.5) 178 (15.2) 864 (56.5) 495 (42.4) < .001 Total 757 (28.1) 136 (5.0) 446 (16.5) 1359 (50.4) More than half of the participants aged 35-100-years had severe to extremely severe stress (55.0%), more than half of the females had severe to extremely severe stress (52.6%), and almost one-third of the widowed/divorced participants had severe to extremely severe stress (62.0%). Less than half of the participants living in rural areas had severe to extremely stress (44.3%), and more than one-quarter of the participants who had low economic status had no stress (29.6%). There was a significant relationship between presence of severe/extremely severe stress and (i) age (more prevalent among older participants), (ii) gender (more prevalent among females), (iii) marital status (more prevalent among married and widow/divorced participants) (iv) residency (more prevalent among residents living in rural areas), (v) education (more prevalent among illiterate participants), (vi) economic status (more prevalent among participants with low income economic status), and (vii) bad events (more prevalent among participants who experienced a bad event during the past month [Table 4 ]. Table 4 Association of stress with participants socio-demographic characteristics (n = 2698) Characteristic Stress p -value Normal Mild Moderate Ex/Severe N (%) N (%) N (%) N (%) Age group 15–34-years 35–100-years 737 (38.3) 167 (21.6) 197 (10.2) 43 (5.6) 295 (15.3) 138 (17.8) 695 (36.1) 426 (55.0) < .001 Gender Male Female 545 (44.2) 359 (24.5) 125 (10.1) 115 (7.9) 213 (17.3) 220 (15.0) 351 (28.4) 770 (52.6) < .001 Marital status Single Married Widow/divorced 399 (43.9) 488 (28.4) 17 (23.9) 108 (11.9) 129 (7.5) 3 (4.2) 152 (16.7) 274 (15.9) 7 (9.9) 250 (27.5) 827 (48.1) 44 (62.0) < .001 Residency Urban Rural 641 (35.7) 263 (29.2) 180 (10.0) 60 (6.7) 255 (14.2) 178 (19.8) 722 (40.2) 399 (44.3) < .001 Education Illiterate Primary school Secondary school High school University 168 (17.9) 103 (31.6) 167 (35.5) 281 (47.8) 185 (49.1) 52 (5.6) 27 (8.3) 37 (8.3) 37 (7.9) 71 (12.1) 144 (15.4) 63 (19.3) 82 (17.4) 86 (14.6) 58 (15.4) 572 (61.1) 133 (40.8) 185 (39.3) 150 (25.5) 81 (21.5) < .001 Economic status High income Middle income Low income 58 (63.7) 199 (47.4) 647 (29.6) 8 (8.8) 50 (11.9) 182 (8.3) 8 (8.8) 73 (17.4) 352 (16.1) 17 (18.7) 98 (23.3) 1006 (46.0) < .001 Cigarette smoking Never smoked Ex-smoker Current smoker 822 (33.8) 51 (32.5) 31 (29.0) 210 (8.6) 19 (12.1) 11 (10.3) 368 (15.1) 41 (26.1) 24 (22.4) 1034 (42.5) 46 (29.3) 41 (38.3) .001 Bad event occurring in the past month Yes No 396 (25.9) 508 (43.5) 131 (8.6) 109 (9.3) 253 (16.5) 180 (15.4) 750 (49.0) 371 (31.8) < .001 Total 904 (33.5) 240 (8.9) 433 (16.0) 1121 (41.5) Multiple logistic regression analysis was performed to see which variables predicted depression, anxiety, and stress. The variables that were significantly associated with depression were: gender (being female) (AOR = 1.746, p < 0.001), economic status (having a low income) (AOR = 2.627, p < 0.001), residency (living in a rural area) (AOR = 1.233, p = 0.043), education (being university level) (AOR = 0.345, p < 0.001), cigarette smoking (current-smoker) (AOR = 2.785, p < 0.001) and a bad event occurring in the past month (AOR = 0.436, p < 0.001). The variables that were significantly associated with anxiety were: age (being older) (AOR = 1.526, p < 0.001), gender (being female) (AOR = 1.716, p < 0.001), economic status (having a low income) (AOR = 2.080, p = 0.002), residency (living in a rural area) (AOR = 1.262, p = 0.029), education (being university level) (AOR = 0.237, p < 0.001), cigarette smoking (current-smoker) (AOR = 2.496, p < 0.001) and a bad event occurring in the past month (AOR = 0.416, p < 0.001). The variables that were significantly associated with stress were: gender (being female) (AOR = 2.353, p < 0.001), economic status (having a low income) (AOR = 2.747, p < 0.001), education (being university level) (AOR = 0.265, p < 0.001), cigarette smoking (current smoker) (AOR = 2.521, p < 0.001), and a bad event occurring in the past month (AOR = 0.449, p < 0.001). [ Table 5 ] Table 5 Multiple logistic regression analysis of depression, anxiety and stress on participants’ sociodemographic characteristics in Afghanistan (n = 2698) Variable Depression Anxiety Stress AOR [95% CI] p -value AOR [95% CI] p -value AOR [95% CI] p- value Age group 15–34-years Reference Reference Reference 35–100-years 1.211 [0.950, 1.543] .122 1.526 [1.182, 1.972] .001 1.250 [0.990, 1.578] .061 Gender Male Reference Reference Reference Female 1.762 [1.463, 2.123] < .001 1.716 [1.419, 2.074] < .001 2.353 [1.963, 2.820] < .001 Economic status High income Reference Reference Reference Middle income 1.586 [1.257, 2.002] < .001 1.618 [1.279, 2.047] .002 1.613 [1.281, 2.031] < .001 Low income 2.627 [1.669, 4.136] < .001 2.080 [1.315, 3.292] < .001 2.747 [1.717, 4.395] < .001 Residency Urban Reference Reference Reference Rural 1.233 [1.007, 1.511] .043 1.262 [1.025, 1.554] .029 1.042 [0.858, 1.265] .678 Education Illiterate Reference Reference Reference Primary school 0.913 [0.691, 1.205] .519 0.904 [0.686, 1.190] 0.471 0.923 [0.701, 1.215] 0.568 Secondary school 0.593 [0.438, 0.802] .001 0.524 [0.388, 0.708] < .001 0.577 [0.430, 0.775] < .001 High school 0.466 [0.330, 0.659] < .001 0.403 [0.285, 0.570] < .001 0.488 [0.351, 0.679] < .001 University 0.345 [0.254, 0.469] < .001 0.237 [0.173, 0.324] < .001 0.265 [0.196, 0.358] < .001 Cigarette smoking Never smoked Reference Reference Reference Ex-smoker 1.724 [0.919, 3.237] .090 1.790 [0.970, 3.304] .063 1.632 [0.923, 2.885] .092 Current smoker 2.785 [1.663, 4.666] < .001 2.496 [1.514, 4.115] < .001 2.521 [1.589, 3.999] < .001 Traumatic event Yes Reference Reference Reference No 0.436 [0.364, 0.523] < .001 0.412 [0.343, 0.496] < .001 0.449 [0.376, 0.536] < .001 Discussion The mental health of Afghans living under Taliban rule is a matter of the utmost importance, and it is essential to understand some of the complex factors contributing to this issue. The Taliban's return to power in Afghanistan has brought about significant political, social, and economic changes that appear to have had a profound impact on the well-being of the Afghan population [ 25 , 26 ]. Several studies have reported severe anxiety, depression and stress among the Afghan people but these have been localized studies and/or included a specific proportion of the Afghan society [ 22 , 23 , 27 ]. The present national survey was carried out to examine the mental health issues faced by Afghan people and determine the socio-demographic factors associated stress, anxiety, and depression. In the present study, less than one-fifth of the participants (18.9%) did not exhibit any signs of depression, anxiety, or stress. In the present study, approximately one-fifth of the participants (27.9%) indicated a mental state free of any depression symptoms, with females exhibiting a higher prevalence of depressive symptoms (77.6%) than males (65.5%). Consistent with previous research, gender emerged as a significant factor influencing mental health status, with females manifesting elevated levels of mental health disorders compared to males [ 23 , 28 ]. The findings indicated that 64.5% of those reporting depression symptoms also reported anxiety symptoms. Moreover, 62.0% of individuals reporting depressive symptoms also reported experiencing stress. Factors significantly associated with depression included age (being older), gender (being female), marital status (being widow/divorced), residency (residing in rural areas), education level (having lower educational attainment), economic status (having a low monthly income), cigarette smoking (being a current smoker), and experiencing a bad event in the past month. The prevalence of depressive symptoms in the present study is much higher than the reported range by the World Health Organization (WHO), which indicates a frequency of 1 in 10 individuals in areas affected by conflict. However, the present study found a markedly elevated prevalence of nearly 7 in 10 individuals, greatly surpassing the figures by the WHO [ 15 ]. Those aged over 34 years, exhibited a much higher prevalence of depressive symptoms (81.1%) compared to the younger age group aged under 35 years (68.4%). In comparison, data from a 2019 interview survey conducted by the Centers for Disease Control and Prevention (CDC) in the US indicated that 21.0% of adults aged 18–29 years experienced depressive symptoms, compared to 16.8% among adults aged 30–44 years [ 29 ]. The disparity in depressive symptoms between age groups may reflect differences in life stressors, financial burdens, and social isolation, with older individuals potentially facing more complex challenges. The findings of this study align with a previous study which reported 79.0% depression among women in Afghanistan (79.0%) [ 22 ]. This suggests that depression symptoms remained the same even after the war ended in Afghanistan. This finding is consistent with another study which found that psychological distress symptoms were prevalent among 75% of the national Afghan population [ 30 ], but much higher than a study among Afghan pregnant women which reported the prevalence of depression to be 60.9% [ 31 ], Compared to countries elsewhere in the world, a systematic review by Mahmud et al. [ 32 ] examining depression during COVID-19 indicated that 30.5% of the global population exhibited symptoms of depression. These findings suggest that in Afghanistan, the prevalence of depression exceeds that of the global average. Notably, under the Taliban government, there has been a slight increase in this prevalence. Moreover, in the present study, the presence of depressive symptoms was significantly associated with educational attainment, with illiterate participants reporting a higher prevalence (83.2%) compared to those with a university education (58.6%). This is in line with findings of previous study in Afghanistan that reported a significant association between educational level and presence of depression symptoms [ 23 ]. This finding also aligns with a European study that reported higher levels of education being associated with lower odds of depression [ 33 ]. A meta-analysis further supports the crucial role of educational levels in shaping mental health outcomes, including depression, showing that those with lower education have poorer mental health outcomes [ 34 ]. Almost three-quarters of participants reported anxiety symptoms (71.9%) with those aged over 34 years reporting a higher prevalence (84.9%), in contrast to those aged under 35 years (66.7%). This is in line with findings of a previous study among women in Afghanistan (n = 438) which reported that the prevalence of anxiety among older participants (75.6%) was higher than younger ones (89.1%) [ 23 ], a finding that is generally supported in the literature [ 22 – 23 ]. This differs from findings in a study conducted in Iran (n = 7886), where the prevalence of anxiety was reported to be higher among younger participants (20.1%) than older participants (13.8%) [ 35 ]. Additionally, a study conducted in Malaysia (n = 506) reported higher levels of anxiety in the younger age group (9.61%) compared to old age groups (12.8%) [ 36 ]. A meta-analysis by Mahmud et al. reported that 29.6% of the world population during the COVID-19 pandemic had anxiety [ 32 ]. This suggests that compared to the rest of the world, anxiety appears to be more prevalent in Afghanistan. The different rate observed in the present study’s findings compared to other studies may be due to cultural, geographic, and methodological differences, impacting the manifestation and disclosure of anxiety symptoms across distinct demographic cohorts and locales. Marital status emerged as another significant factor associated with anxiety symptoms, with widowed/divorced participants reporting the highest percentage of anxiety (85.9%) compared to the other two groups (61.3% single and 77.0% married). This aligns with prior systematic reviews indicating that being divorced or widowed are significant predictors of anxiety among women [ 33 , 37 ]. This is in line with previous study in Afghanistan (n = 438) which reported higher prevalence of anxiety among divorced participants compared to single and married participants [ 23 ]. With regards to educational attainment, participants with at least a university-level education reported the lowest levels of anxiety (55.2%), while a significantly higher proportion of illiterate participants reported anxiety symptoms (87.0%). This observation aligns with a previous study in India (n = 180) indicating an increased likelihood of anxiety among women with lower educational attainment [ 38 ]. Moreover, in the present study, specific demographic subgroups reported elevated anxiety levels compared to their counterparts. More specifically, those with a low family monthly income recorded a higher prevalence of anxiety (75.7%) in comparison to those with a high family monthly income (47.3%). This finding is in line with the findings of a previous study in Afghanistan (n = 664) that reported higher prevalence of anxiety among low monthly family income participants compared to high income monthly family income [ 22 ]. Additionally, individuals who experienced a negative event in the past month reported higher anxiety levels (79.4%) compared to those who did not (62.2%). These findings align with the findings of previous aforementioned study in Afghanistan that reported higher prevalence of anxiety among participants who experienced negative event in the past month than those who had not [ 23 ]. Over half of participants aged over 34 years (55%) reported symptoms of stress. The study found significant associations between various demographic factors and stress, including gender, age group, marital status, residency, traumatic experiences, and economic status. More specifically, the findings indicated that older individuals, females, and those with lower income levels reported more stress than their counterparts. These findings are novel as no previous study in Afghanistan has assessed the prevalence of stress among the general population. However, studies have been conducted on the mental health of healthcare workers [ 39 ], adolescents [ 40 ], and women in Afghanistan [ 22 ]. These results diverge from those of a systematic review conducted by Salari et al. among general population [ 41 ], which identified a negative association between stress and the age group of participants (n = 9074). In the present study, prevalence of stress was found at 66.49%. This is much higher than the findings of two systematic reviews by Mahmud et al. [ 32 ] and Salari et al. [ 41 ] who reported that during the COVID-19 pandemic, the prevalence of stress was 29.4% and 29.6% globally, respectively [ 32 ]. In the present study, a higher prevalence of stress was observed among married participants (71.6%) compared to their single counterparts (56.1%). This contrasts with findings in a study by Cao et al. in China [ 42 ], where prevalence of stress among single marital status was higher than married participants (n = 9030). Moreover, the impact of traumatic experiences on individuals' lives cannot be understated [ 43 ], and the findings of the present study reinforce existing evidence that individuals with a history of traumatic events are more susceptible to the development of stress [ 27 , 44 – 45 ]. These findings underscore the intricate interplay between demographic variables, life experiences, and stress manifestation, contributing valuable insights to the understanding of stress dynamics within diverse populations. Multiple regression analysis indicated that gender (being female), economic status (being poor), residency (living in rural areas), education level (being illiterate), being a cigarette smoker, and having experienced a traumatic event during the past month were significantly associated with depression, anxiety and stress. These findings underscore the interplay of these demographic and behavioral factors in influencing the manifestation of mental health symptoms. Importantly, extant literature has consistently corroborated the significant impact of depression on these specific demographic factors, as evidenced by prior studies [ 46 – 50 ], further affirming the robustness of the present study’s findings. The study’s findings also indicate the multifaceted nature of the possible determinants of anxiety symptoms, providing insight into the interconnectedness of various demographic and behavioral elements. Notably, existing research has consistently highlighted the substantial impact of anxiety on the aforementioned demographic factors, as substantiated by a body of literature spanning prior investigations [ 51 – 57 ]. A significant proportion of cigarette smokers in the present study (80.4%) exhibited indications of depressive symptoms. Additionally, 77.6% of current smokers displayed symptoms indicative of anxiety, while 71.0% reported experiencing symptoms associated with stress. Current smokers exhibited a prevalence of depressive symptoms 2.8 times greater than individuals who had never smoked. Similarly, they displayed a prevalence of anxiety symptoms 2.5 times higher and a prevalence of stress symptoms 2.5 times higher compared to individuals who had never smoked. These findings are in line with results of a systematic review conducted by Fluharty et al. which reported that smoking was associated with depression and anxiety [ 58 ]. Other systematic reviews have reported that smoking is associated with depression [ 59 ] and anxiety [ 60 ], and that the relationships are bi-directional, and that one can lead to another [ 59 – 60 ]. It is noteworthy that the present study’s findings resonate with broader trends observed in the national Afghan landscape. A study conducted in major provinces of Afghanistan in 2021 (n = 664) reported that almost four-fifths of Afghan women exhibited depression symptoms (79.1%) [ 22 ]. This alignment of findings suggests an increase in high prevalence of mental health disorders among the Afghan population. Limitations The present study had a number of limitations. Firstly, the study lacked an assessment of the onset dates of depression, anxiety, and/or stress, precluding the determination of whether participants' mental health conditions changed post-Taliban takeover or had pre-existing origins. Notably, the reliance on self-reported data introduces potential methodological biases, despite providing estimates of depression, anxiety, and stress among the Afghan population and their associations with socio-demographic factors. The cross-sectional design of the study further restricts the capacity to determine causality between the examined variables. Furthermore, the non-representative nature of the sample is a limitation because it encompasses participants from only three regions in Afghanistan, with an overrepresentation of urban residents compared to the national distribution. Consequently, the sample exhibits a disproportionately lower proportion of illiterate participants than the national demographic composition, undermining the generalizability of the study's findings to all Afghans. The scarcity of previous investigations into the mental health of the general Afghan population since the resurgence of the Taliban hindered the ability to contextualize and compare the results of the present study with other studies, limiting the discernment of meaningful trends. Conclusion and recommendations The mental health crisis in Afghanistan is a complex and urgent issue that requires a comprehensive and compassionate response. The findings of the present study showed very high levels of anxiety, depression, and stress among the participants. The study offered important insights into the mental health status of Afghans living under the Taliban government. The high prevalence rates of depression, anxiety, and stress underscore the substantial psychological burden experienced by the population. The identified socio-demographic factors, such as being female, being of low economic status, living in rural regions, having a low education level, being a cigarette smoker, and recent traumatic experiences, highlight the complexity of mental health disparities in this context. These findings emphasize the pressing need for targeted and culturally sensitive interventions to address the multifaceted challenges contributing to the high prevalence of mental health disorders. Tailored mental health programs, informed by the findings here, could play a pivotal role in mitigating the impact of psychological distress and promoting overall well-being among Afghans living under the current sociopolitical circumstances. The findings of the present study suggest a potential comorbidity between mental health disorders and various socio-demographic vulnerabilities among Afghans, necessitating urgent attention to address the prevailing mental health challenges under the current Taliban governance. Subsequent research endeavors should explore the origins of therapeutic resources and assess their accessibility within the broader Afghan population. Moreover, as the international community engages with Afghanistan, it must prioritize the well-being of the Afghan individuals and provide the necessary resources to address their mental health needs. This includes providing funding for mental health services, training local mental health professionals, and raising awareness about mental health issues to reduce stigma. Declarations Consent for publication Not applicable Ethical considerations The Afghanistan Center for Epidemiological Studies – Ethical Committee granted ethical clearance for the implementation of this study (reference number #23.1.039). Subsequent to initial engagement with participants, a comprehensive overview of the study was provided. Consent, whether written or verbal, was procured from all participants involved in the study. For participants under the age of 18, consent was obtained from their parents. Participants were duly informed of their right to withdraw from the study at any juncture. All methodologies employed in this study adhere to the principles outlined in the Declaration of Helsinki. Declaration of Interests: Authors of this study declare that there is no competing interest. Funding: This study did not receive external funding. Author Contribution AN and AQM designed the study. NR, BAR, SS, NRa, and ZT collected the data. AN, and PS analyzed the data. AN, AQM, NR, PS and BAR prepared the draft of the manuscript. AN, BAR and MG critically reviewed, rewrote, edited, and finalized the manuscript. All authors reviewed the manuscript. Acknowledgement: We would like to express our sincere gratitude to all the participants who enrolled in this study. 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Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 02 May, 2024 Reviews received at journal 27 Apr, 2024 Reviews received at journal 16 Apr, 2024 Reviewers agreed at journal 15 Apr, 2024 Reviewers agreed at journal 13 Apr, 2024 Reviewers invited by journal 13 Apr, 2024 Editor assigned by journal 12 Apr, 2024 Submission checks completed at journal 12 Apr, 2024 First submitted to journal 22 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4149818","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":293599248,"identity":"7a451f0f-273b-4667-ac6d-df405f2623a2","order_by":0,"name":"Ahmad Neyazi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYNACAwYGfiiTH69CFC2SDRAmjCZG1wFitZiz9xh+/FHAIG98/PDDhz8Y7CQY2Hsfv8CnxbLnjLGEhAGD4bYzacbGPAzJEgw8x80s8LrnRo6BhIEBA+O2Azls0oz/mOsYJNLYDPBquf/G+EeCAYP95v437D9/MNRLENZyg8dM4oABQ+IGiRw2Bh6GwyAtzA/wajmTVmbZYCCRPOPGM2NpHobjEmw8x9jw6WAwOH54880ff2xs+/uTH378wVAtwc/exvwBrx4GDpDDJRB8oBVsEjhVgwE7psMJ2TIKRsEoGAUjDAAAePtASo5zg8UAAAAASUVORK5CYII=","orcid":"","institution":"Afghanistan Center for Epidemiological Studies","correspondingAuthor":true,"prefix":"","firstName":"Ahmad","middleName":"","lastName":"Neyazi","suffix":""},{"id":293599249,"identity":"ce27e0f7-9527-4ec9-8c18-e71d29e680aa","order_by":1,"name":"Abdul Qadim Mohammadi","email":"","orcid":"","institution":"Herat Regional Hospital","correspondingAuthor":false,"prefix":"","firstName":"Abdul","middleName":"Qadim","lastName":"Mohammadi","suffix":""},{"id":293599250,"identity":"ad85cc9c-c9df-41cb-9c50-503c86129a80","order_by":2,"name":"Nosaibah Razaqi","email":"","orcid":"","institution":"Afghanistan Center for Epidemiological Studies","correspondingAuthor":false,"prefix":"","firstName":"Nosaibah","middleName":"","lastName":"Razaqi","suffix":""},{"id":293599251,"identity":"439f5371-4e45-4836-90b9-892966f4e25c","order_by":3,"name":"Bilal Ahmad Rahimi","email":"","orcid":"","institution":"Kandahar University","correspondingAuthor":false,"prefix":"","firstName":"Bilal","middleName":"Ahmad","lastName":"Rahimi","suffix":""},{"id":293599252,"identity":"2e8e8260-3b11-43d9-a115-34d06736f502","order_by":4,"name":"Sifatullah Sifat","email":"","orcid":"","institution":"Dr Shams-ul-Haq Kakar Comprehensive Health Center","correspondingAuthor":false,"prefix":"","firstName":"Sifatullah","middleName":"","lastName":"Sifat","suffix":""},{"id":293599253,"identity":"ad929bd0-6d43-4b5a-9f9d-674e43e81e14","order_by":5,"name":"Najeebullah Rahimy","email":"","orcid":"","institution":"Kandahar University","correspondingAuthor":false,"prefix":"","firstName":"Najeebullah","middleName":"","lastName":"Rahimy","suffix":""},{"id":293599254,"identity":"4851cdd7-8bab-4a67-81ae-45bc69b08887","order_by":6,"name":"Zarghoon Tareen","email":"","orcid":"","institution":"Kandahar University","correspondingAuthor":false,"prefix":"","firstName":"Zarghoon","middleName":"","lastName":"Tareen","suffix":""},{"id":293599255,"identity":"280d6c30-76e1-4f84-b908-41aeade6fc91","order_by":7,"name":"Qasim Mehmood","email":"","orcid":"","institution":"King Edward Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qasim","middleName":"","lastName":"Mehmood","suffix":""},{"id":293599256,"identity":"b4e1389a-7909-4407-8611-e723303cf86b","order_by":8,"name":"Prakasini Satapathy","email":"","orcid":"","institution":"Saveetha Medical College and Hospital, Saveetha University","correspondingAuthor":false,"prefix":"","firstName":"Prakasini","middleName":"","lastName":"Satapathy","suffix":""},{"id":293599257,"identity":"61d3b861-39d7-41ba-9ae9-b537c075a758","order_by":9,"name":"Mark D. Griffiths","email":"","orcid":"","institution":"Nottingham Trent University","correspondingAuthor":false,"prefix":"","firstName":"Mark","middleName":"D.","lastName":"Griffiths","suffix":""}],"badges":[],"createdAt":"2024-03-22 12:41:56","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4149818/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4149818/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55529042,"identity":"7dee7731-100c-40ae-8416-83e9fc978687","added_by":"auto","created_at":"2024-04-29 15:20:24","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":253324,"visible":true,"origin":"","legend":"\u003cp\u003eProvinces included in the present study. (The blue color denotes the provinces included in the study, while the black color indicates the provinces where data collection was not carried out)\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4149818/v1/d95ce965dae951635ccdfee4.jpeg"},{"id":55529043,"identity":"8aebecb1-570d-4396-81ab-107d8d98b3e7","added_by":"auto","created_at":"2024-04-29 15:20:24","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":273771,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCategories of depression, anxiety, and stress (Afghanistan-2023)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4149818/v1/a559229d46d52355e3505bfb.jpeg"},{"id":55529801,"identity":"5be12160-9e23-42a0-8fc1-9c8ca94c0410","added_by":"auto","created_at":"2024-04-29 15:28:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":719020,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4149818/v1/8b323805-0b0a-4467-92b2-d0f36116ab9b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Health survey on anxiety, depression, and stress in Afghanistan: A large-scale cross-sectional survey study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAfghanistan, located in South Asia, has been a region of significant political and geopolitical importance for decades. The country has experienced a tumultuous history, marked by conflicts, foreign interventions, and political changes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. One of the most significant events in recent Afghan history is the rise of the Taliban and the war that followed, which had profound impacts on the lives of Afghans [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Taliban is an extremist Islamist group that emerged in the early 1990s. They gained control of Afghanistan in 1996, imposing a strict interpretation of Islamic law. Following the 9/11 attacks in the United States in 2001, the U.S. and its allies initiated Operation Enduring Freedom to oust the Taliban regime and dismantle Al-Qaeda [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The war evolved into a protracted conflict, characterized by insurgency, counterinsurgency efforts, and complex alliances with Afghan factions [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAfter the fall of the Taliban in 2001, efforts were made to rebuild Afghanistan, establish democratic institutions, and promote human rights and gender equality. Despite these efforts, corruption, political instability, and a resurgent Taliban posed ongoing challenges to the nation's development. However, in August 2021, the Taliban regained control of the country as United States and NATO forces withdrew, leading to concerns about the protection of human rights and the Afghan people's future [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Afghan conflict has had far-reaching global implications, influencing regional stability, refugee crises, and counterterrorism efforts [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The situation in Afghanistan is highly fluid, and the well-being of its citizens remain a global concern. The complex history of Afghanistan, the rise of the Taliban, and the enduring war have left a deep impact on the lives of Afghans, shaping the country's destiny and its place in the world [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe mental health of the Afghan people has long been a matter of concern due to decades of conflict and instability in the region. The return of the Taliban to power in Afghanistan in recent years has raised new and urgent questions about the well-being of its citizens [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Afghanistan has been marred by war and violence for generations. The resurgence of the Taliban has the potential to trigger or exacerbate trauma among individuals who have experienced violence, displacement, and loss [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Post-traumatic stress disorder (PTSD) is a significant concern, given the cumulative effects of prolonged conflict [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe uncertainty associated with Taliban rule, especially concerning women's rights, freedom of expression, and personal freedoms, appears to have generated widespread anxiety and fear among Afghan citizens [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Living under strict rules and facing harsh consequences for non-compliance can take a significant toll on individuals\u0026rsquo; mental well-being. The loss of livelihoods, the breakdown of essential services, and the general sense of hopelessness can lead to high rates of depression among the Afghan population [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Furthermore, the lack of economic prospects and the absence of a stable environment can contribute to a sense of despair [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMental health issues are often stigmatized in Afghan society, making it challenging for individuals to seek help or confide in others [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The fear of being ostracized or labeled as weak can lead to social isolation for those grappling with mental health challenges [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Also, the country is facing significant hurdles in providing mental health services to the Afghan people. Conflict and instability have strained the healthcare system, making it difficult for individuals to access the support they need. The current situation has likely exacerbated this issue, leaving many without proper care [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Furthermore, the condition of Afghan women under Taliban rule cannot be underestimated. Gender-based violence, forced marriages, and the fear of losing access to education and employment can lead to severe anxiety, depression, and trauma among women [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWith approximately 90% of the Afghan population experiencing the deleterious effects of poverty [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], the plight of women and girls has become even more pronounced [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Under the governance of the Taliban, women encounter constraints in various domains, including education, employment, mobility, political involvement, healthcare access, and public visibility [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. These circumstances have the potential to exacerbate pre-existing mental health disorders among the populace. Additionally, the advent of COVID-19, coupled with other contributing factors (e.g., poverty), is likely to have adversely affected mental well-being [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The closure of numerous schools and daycare facilities has compelled women to shoulder additional responsibilities, including the care of children and/or elderly family members, often concurrently managing remote work obligations [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This heightened workload has the potential to engender feelings of fatigue, frustration, and burnout, collectively posing a considerable threat to mental health [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the aforementioned research, there has been no prior research examining the levels of depression, anxiety, and stress experienced by Afghans at a national level during the Taliban's governance. Therefore, the present study examined these mental health aspects collectively among Afghans. Additionally, it explored the underlying factors associated with depression, anxiety, and stress. Lastly, the study examined how socio-demographic traits of Afghans under Taliban rule relate to these three mental health indicators. As the study was exploratory, there were no specific hypotheses\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants, study design, and procedure\u003c/h2\u003e \u003cp\u003eBetween June 5, 2023 and February 12, 2024, a cross-sectional study was conducted. The study comprised 2,698 participants (1234 men and 1464 women), ranging in age from 15 to 100 years (mean age\u0026thinsp;=\u0026thinsp;30.96 years; SD\u0026thinsp;\u0026plusmn;\u0026thinsp;13.70). These participants were recruited from various regions in Afghanistan, namely the southern region (Kandahar, Helmand), western region (Herat, Badghis, Farah, Ghor), and northern region (Mazar-e-Sharif, Samangan) [Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e]. Data were collected through face-to-face interviews conducted by 15 trained data collectors. Participants were recruited using cluster convenience sampling. A total of 3080 individuals residing in the aforementioned provinces were directly invited to participate in the study by approaching them outdoors in streets where they lived and/or worked. Among these, 2698 individuals volunteered to be interviewed (response rate\u0026thinsp;=\u0026thinsp;87.6%).\u003c/p\u003e \u003cp\u003eTo be eligible for the study, individuals had to meet specific criteria. More specifically, they had to be: (i) residents of Afghanistan, (ii) aged at least 15 years, (iii) able to understand either Dari or Pashto languages, and (iv) able to provide either written or verbal informed consent (those aged 15\u0026ndash;18 years were also required to have additional consent from their parents). The target sample size was determined using the formula N\u0026thinsp;=\u0026thinsp;Zα2P(1\u0026thinsp;\u0026minus;\u0026thinsp;P)/d2, with α\u0026thinsp;=\u0026thinsp;0.05 and Zα\u0026thinsp;=\u0026thinsp;1.96, and a margin of error (d) of 5% which means the minimum sample size for each cluster (province) was 385. The proportion of women experiencing depression and anxiety was estimated at 80% based on existing Afghan literature [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. No recent prevalence estimates exist for males. OpenEpi software (v3.01) was employed to calculate the sample size.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eInstruments\u003c/h2\u003e \u003cp\u003eThe present study utilized a survey comprising two sections: one focused on socio-demographic information and the other on mental health issues (i.e., assessing depression, anxiety, and stress levels). The socio-demographic section comprised questions relating to age, marital status, residency, education level, economic status, cigarette smoking status, and whether participants had experienced a bad event in the past month (defined as any action or occurrence that occurred within the past month that led the participant to feel down or depressed). The interpretation of what constituted a \u003cem\u003e\"bad event\"\u003c/em\u003e was left to the participants.\u003c/p\u003e \u003cp\u003eTo assess participants' levels of depression, anxiety, and stress, the Persian version of the 21-item Depression Anxiety Stress Scale (DASS-21) was employed [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The scale is divided into three sub-domains: depression, anxiety, and stress. Responses for all items, such as \u003cem\u003e\"I couldn't seem to experience any positive feeling at all\"\u003c/em\u003e are scored on a scale from 0 (\u003cem\u003e\"Did not apply to me at all\"\u003c/em\u003e) to 3 (\u003cem\u003e\"Applied to me very much or most of the time\"\u003c/em\u003e). Scores for each sub-domain range from 0 to 21. To obtain the final score for each sub-domain, the score was multiplied by two, resulting in the same scoring as the longer DASS-42. For the depression sub-domain, the standard cut-off scores were applied: 0 to 9 indicated normal levels, 10 to 13 indicated mild depression, 14 to 20 indicated moderate depression, and scores above 20 indicated severe to extremely severe depression symptoms. In the present study, Cronbach\u0026rsquo;s alpha for the depression subscale was 0.849. Similarly, for the anxiety sub-domain, scores between 0 to 7 are considered normal, 8 to 9 indicate mild anxiety, 10 to 14 indicate moderate anxiety, and scores higher than 14 indicate severe to extremely severe anxiety symptoms. Cronbach\u0026rsquo;s alpha for anxiety subscale in the present study was 0.836. For the stress sub-domain, scores between 0 to 14 are considered normal, 15 to 18 indicate mild stress, 19 to 25 indicate moderate stress, and scores higher than 25 indicate severe to extremely severe stress symptoms. Cronbach\u0026rsquo;s alpha for the stress subscale in the present study was 0.874.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis\u003c/h2\u003e \u003cp\u003eThe data were entered using Microsoft Excel 2016, while the analysis was conducted using IBM SPSS version 26.0 for Windows. Descriptive statistics comprised means, standard deviations, frequencies, and percentages. Associations between variables were assessed utilizing chi-square tests. To explore the independent socio-demographic factors associated with depression, anxiety, and stress, a multiple regression analysis was employed. Variables with a \u003cem\u003ep\u003c/em\u003e-value below 0.05 were considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf the 2698 participants, more than half of participants were female (54.3%), almost two-thirds of the participants were married (63.7%), and two-thirds of the participants were living in urban areas (66.6%). One-eighth of the participants had university level education (14.0%), and more than four-fifths of the participants had low-income economic status (81.0%). One-tenth had ever smoked while nine-tenths of the participants had never smoked (90.2%). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides a detailed breakdown of the participants\u0026rsquo; characteristics [Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics distribution of the study sample (n\u0026thinsp;=\u0026thinsp;2698)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u0026ndash;34-years\u003c/p\u003e \u003cp\u003e35\u0026ndash;100-years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e914\u003c/p\u003e \u003cp\u003e320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.5\u003c/p\u003e \u003cp\u003e41.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1010\u003c/p\u003e \u003cp\u003e454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52.5\u003c/p\u003e \u003cp\u003e58.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1924\u003c/p\u003e \u003cp\u003e774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e71.3\u003c/p\u003e \u003cp\u003e28.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSingle\u003c/p\u003e \u003cp\u003eMarried\u003c/p\u003e \u003cp\u003eWidow/divorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e465\u003c/p\u003e \u003cp\u003e759\u003c/p\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.2\u003c/p\u003e \u003cp\u003e44.2\u003c/p\u003e \u003cp\u003e14.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e444\u003c/p\u003e \u003cp\u003e959\u003c/p\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48.8\u003c/p\u003e \u003cp\u003e55.8\u003c/p\u003e \u003cp\u003e85.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e909\u003c/p\u003e \u003cp\u003e1718\u003c/p\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33.7\u003c/p\u003e \u003cp\u003e63.7\u003c/p\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e769\u003c/p\u003e \u003cp\u003e465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.8\u003c/p\u003e \u003cp\u003e51.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1029\u003c/p\u003e \u003cp\u003e435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.2\u003c/p\u003e \u003cp\u003e48.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1798\u003c/p\u003e \u003cp\u003e900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e66.6\u003c/p\u003e \u003cp\u003e33.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003cp\u003ePrimary school\u003c/p\u003e \u003cp\u003eSecondary school\u003c/p\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e329\u003c/p\u003e \u003cp\u003e162\u003c/p\u003e \u003cp\u003e242\u003c/p\u003e \u003cp\u003e324\u003c/p\u003e \u003cp\u003e177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.1\u003c/p\u003e \u003cp\u003e49.7\u003c/p\u003e \u003cp\u003e51.4\u003c/p\u003e \u003cp\u003e55.1\u003c/p\u003e \u003cp\u003e46.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e607\u003c/p\u003e \u003cp\u003e164\u003c/p\u003e \u003cp\u003e229\u003c/p\u003e \u003cp\u003e264\u003c/p\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e64.9\u003c/p\u003e \u003cp\u003e50.3\u003c/p\u003e \u003cp\u003e48.6\u003c/p\u003e \u003cp\u003e44.9\u003c/p\u003e \u003cp\u003e53.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e936\u003c/p\u003e \u003cp\u003e326\u003c/p\u003e \u003cp\u003e471\u003c/p\u003e \u003cp\u003e588\u003c/p\u003e \u003cp\u003e377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34.7\u003c/p\u003e \u003cp\u003e12.1\u003c/p\u003e \u003cp\u003e17.4\u003c/p\u003e \u003cp\u003e21.8\u003c/p\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEconomic status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh income\u003c/p\u003e \u003cp\u003eMiddle income\u003c/p\u003e \u003cp\u003eLow income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003cp\u003e196\u003c/p\u003e \u003cp\u003e984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.3\u003c/p\u003e \u003cp\u003e46.7\u003c/p\u003e \u003cp\u003e45.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37\u003c/p\u003e \u003cp\u003e224\u003c/p\u003e \u003cp\u003e1203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.7\u003c/p\u003e \u003cp\u003e53.3\u003c/p\u003e \u003cp\u003e55.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e91\u003c/p\u003e \u003cp\u003e420\u003c/p\u003e \u003cp\u003e2187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003cp\u003e15.6\u003c/p\u003e \u003cp\u003e81.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCigarette smoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNever smoked\u003c/p\u003e \u003cp\u003eEx-smoker\u003c/p\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1021\u003c/p\u003e \u003cp\u003e120\u003c/p\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41.9\u003c/p\u003e \u003cp\u003e76.4\u003c/p\u003e \u003cp\u003e86.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1413\u003c/p\u003e \u003cp\u003e37\u003c/p\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e58.1\u003c/p\u003e \u003cp\u003e23.6\u003c/p\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2434\u003c/p\u003e \u003cp\u003e157\u003c/p\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e90.2\u003c/p\u003e \u003cp\u003e5.8\u003c/p\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBad event occurring in the past month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e650\u003c/p\u003e \u003cp\u003e584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.5\u003c/p\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e880\u003c/p\u003e \u003cp\u003e584\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.5\u003c/p\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1530\u003c/p\u003e \u003cp\u003e1168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e56.7\u003c/p\u003e \u003cp\u003e43.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1234\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1464\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e2698\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e100.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong the participants, 510 did not exhibit any signs of depression, anxiety, or stress (18.9%). Conversely, 1557 displayed symptoms of all three conditions (57.7%), with 50.3% reporting severe to extremely severe anxiety, 41.5% reporting severe to extremely severe stress, and 38.73% reporting severe to extremely severe depression. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the intersecting prevalence of depression, anxiety, and stress among the study participants [Figure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAlmost half of the participants aged 35-100-years had severe to extremely severe depression (49.7%), less than half of the female participants had severe to extremely severe depression (46.4%), and almost two-thirds of the widowed/divorced participants had severe to extremely severe depression (62.0%). More than one-third of the participants living in urban areas had severe to extremely severe depression (36.1%), and one-quarter of participants who had low economic status had no depression (24.4%). There was a significant relationship between presence of severe to extremely severe depression and (i) age group (more prevalent among elder participants), (ii) gender (more prevalent among females), (iii) marital status (more prevalent among married and widow/divorced participants) (iv) residency (more prevalent among residents living in rural areas), (v) education (more prevalent among illiterate participants), (vi) economic status (more prevalent among participants with low-income economic status), and (vii) bad events (more prevalent among participants who experienced a bad event during the past month [Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of depression with participants socio-demographic characteristics (n\u0026thinsp;=\u0026thinsp;2698)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSevere and extremely severe\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003cp\u003e15\u0026ndash;34-years\u003c/p\u003e \u003cp\u003e35\u0026ndash;100-years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e608 (31.6)\u003c/p\u003e \u003cp\u003e146 (18.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e196 (10.2)\u003c/p\u003e \u003cp\u003e63 (8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e460 (23.9)\u003c/p\u003e \u003cp\u003e180 (23.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e660 (34.3)\u003c/p\u003e \u003cp\u003e385 (49.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e426 (34.5)\u003c/p\u003e \u003cp\u003e328 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e146 (11.8)\u003c/p\u003e \u003cp\u003e113 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e297 (24.1)\u003c/p\u003e \u003cp\u003e343 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e365 (29.6)\u003c/p\u003e \u003cp\u003e680 (46.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003cp\u003eSingle\u003c/p\u003e \u003cp\u003eMarried\u003c/p\u003e \u003cp\u003eWidow/divorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e321 (35.3)\u003c/p\u003e \u003cp\u003e422 (24.6)\u003c/p\u003e \u003cp\u003e11 (15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105 (11.6)\u003c/p\u003e \u003cp\u003e150 (8.7)\u003c/p\u003e \u003cp\u003e4 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e226 (24.9)\u003c/p\u003e \u003cp\u003e402 (23.4)\u003c/p\u003e \u003cp\u003e12 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e257 (28.3)\u003c/p\u003e \u003cp\u003e744 (43.3)\u003c/p\u003e \u003cp\u003e44 (62.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidency\u003c/p\u003e \u003cp\u003eUrban\u003c/p\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e554 (30.8)\u003c/p\u003e \u003cp\u003e200 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e172 (9.6)\u003c/p\u003e \u003cp\u003e87 (9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e423 (23.5)\u003c/p\u003e \u003cp\u003e217 (24.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e649 (36.1)\u003c/p\u003e \u003cp\u003e396 (44.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003cp\u003ePrimary school\u003c/p\u003e \u003cp\u003eSecondary school\u003c/p\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157 (16.8)\u003c/p\u003e \u003cp\u003e77 (23.6)\u003c/p\u003e \u003cp\u003e133 (28.2)\u003c/p\u003e \u003cp\u003e231 (39.3)\u003c/p\u003e \u003cp\u003e156 (41.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (7.8)\u003c/p\u003e \u003cp\u003e26 (8.0)\u003c/p\u003e \u003cp\u003e57 (12.1)\u003c/p\u003e \u003cp\u003e62 (10.5)\u003c/p\u003e \u003cp\u003e41 (10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e200 (21.4)\u003c/p\u003e \u003cp\u003e90 (27.6)\u003c/p\u003e \u003cp\u003e116 (24.6)\u003c/p\u003e \u003cp\u003e143 (24.3)\u003c/p\u003e \u003cp\u003e91 (24.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e506 (54.1)\u003c/p\u003e \u003cp\u003e133 (40.8)\u003c/p\u003e \u003cp\u003e165 (35.0)\u003c/p\u003e \u003cp\u003e152 (25.9)\u003c/p\u003e \u003cp\u003e89 (23.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEconomic status\u003c/p\u003e \u003cp\u003eHigh income\u003c/p\u003e \u003cp\u003eMiddle income\u003c/p\u003e \u003cp\u003eLow income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51 (56.0)\u003c/p\u003e \u003cp\u003e170 (40.5)\u003c/p\u003e \u003cp\u003e533 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (5.5)\u003c/p\u003e \u003cp\u003e48 (11.4)\u003c/p\u003e \u003cp\u003e206(9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (19.8)\u003c/p\u003e \u003cp\u003e110 (26.2)\u003c/p\u003e \u003cp\u003e512 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17 (18.7)\u003c/p\u003e \u003cp\u003e92 (21.9)\u003c/p\u003e \u003cp\u003e936 (42.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCigarette smoking\u003c/p\u003e \u003cp\u003eNever smoked\u003c/p\u003e \u003cp\u003eEx-smoker\u003c/p\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e695 (28.6)\u003c/p\u003e \u003cp\u003e38 (24.2)\u003c/p\u003e \u003cp\u003e21 (19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e226 (9.3)\u003c/p\u003e \u003cp\u003e19 (12.1)\u003c/p\u003e \u003cp\u003e14 (13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e570 (23.4)\u003c/p\u003e \u003cp\u003e42 (26.8)\u003c/p\u003e \u003cp\u003e28 (26.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e943 (38.7)\u003c/p\u003e \u003cp\u003e58 (36.9)\u003c/p\u003e \u003cp\u003e44 (41.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.265\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBad event occurring in the past month\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e315 (20.6)\u003c/p\u003e \u003cp\u003e439 (37.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e146 (9.5)\u003c/p\u003e \u003cp\u003e113 (9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e367 (24.0)\u003c/p\u003e \u003cp\u003e273 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e702 (45.9)\u003c/p\u003e \u003cp\u003e343 (29.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e754 (27.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e259 (9.6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e640 (23.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1045 (38.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAlmost two-thirds of the participants aged 35-100-years had severe to extremely severe anxiety (66.9%), more than half of the female participants had severe to extremely severe anxiety (56.8%), and almost three-quarters of the widowed/divorced participants had severe to extremely anxiety (71.8%). More than half of the participants living in rural areas had severe to extremely anxiety (57.1%), and one-quarter who had low economic status had no anxiety (24.3%). There was a significant relationship between presence of severe/extremely severe anxiety and (i) age (more prevalent among older participants), (ii) gender (more prevalent among females), (iii) marital status (more prevalent among married and widow/divorced participants) (iv) residency (more prevalent among residents living in rural areas), (v) education (more prevalent among illiterate participants), (vi) economic status (more prevalent among participants with low income economic status), and (vii) bad events (more prevalent among participants who experienced a bad event during the past month [Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of anxiety with participants socio-demographic characteristics (n\u0026thinsp;=\u0026thinsp;2698)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEx/Severe\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003cp\u003e15\u0026ndash;34-years\u003c/p\u003e \u003cp\u003e35\u0026ndash;100-years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e640 (33.3)\u003c/p\u003e \u003cp\u003e117 (15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106 (5.5)\u003c/p\u003e \u003cp\u003e30 (3.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e337 (17.5)\u003c/p\u003e \u003cp\u003e109 (14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e841 (43.7)\u003c/p\u003e \u003cp\u003e518 (66.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e429 (34.8)\u003c/p\u003e \u003cp\u003e328 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 (5.1)\u003c/p\u003e \u003cp\u003e73 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e215 (17.4)\u003c/p\u003e \u003cp\u003e231 (15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e527 (42.7)\u003c/p\u003e \u003cp\u003e832 (56.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003cp\u003eSingle\u003c/p\u003e \u003cp\u003eMarried\u003c/p\u003e \u003cp\u003eWidow/divorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e352 (38.7)\u003c/p\u003e \u003cp\u003e395 (23.0)\u003c/p\u003e \u003cp\u003e10 (14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53 (5.8)\u003c/p\u003e \u003cp\u003e82 (4.8)\u003c/p\u003e \u003cp\u003e1 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e160 (17.6)\u003c/p\u003e \u003cp\u003e277 (16.1)\u003c/p\u003e \u003cp\u003e9 (12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e344 (37.8)\u003c/p\u003e \u003cp\u003e964 (56.1)\u003c/p\u003e \u003cp\u003e51 (71.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidency\u003c/p\u003e \u003cp\u003eUrban\u003c/p\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e565 (31.4)\u003c/p\u003e \u003cp\u003e192 (21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90 (5.0)\u003c/p\u003e \u003cp\u003e46 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e298 (16.6)\u003c/p\u003e \u003cp\u003e148 (16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e845 (47.0)\u003c/p\u003e \u003cp\u003e514 (57.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003cp\u003ePrimary school\u003c/p\u003e \u003cp\u003eSecondary school\u003c/p\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e122 (13.0)\u003c/p\u003e \u003cp\u003e77 (23.6)\u003c/p\u003e \u003cp\u003e137 (29.1)\u003c/p\u003e \u003cp\u003e252 (42.9)\u003c/p\u003e \u003cp\u003e169 (44.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (3.2)\u003c/p\u003e \u003cp\u003e13 (4.0)\u003c/p\u003e \u003cp\u003e42 (8.9)\u003c/p\u003e \u003cp\u003e34 (5.8)\u003c/p\u003e \u003cp\u003e17 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e145 (15.5)\u003c/p\u003e \u003cp\u003e64 (19.6)\u003c/p\u003e \u003cp\u003e76 (16.1)\u003c/p\u003e \u003cp\u003e93 (15.8)\u003c/p\u003e \u003cp\u003e68 (18.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e639 (68.3)\u003c/p\u003e \u003cp\u003e172 (52.8)\u003c/p\u003e \u003cp\u003e216 (45.9)\u003c/p\u003e \u003cp\u003e209 (35.5)\u003c/p\u003e \u003cp\u003e123 (32.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEconomic status\u003c/p\u003e \u003cp\u003eHigh income\u003c/p\u003e \u003cp\u003eMiddle income\u003c/p\u003e \u003cp\u003eLow income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48 (52.7)\u003c/p\u003e \u003cp\u003e178 (42.4)\u003c/p\u003e \u003cp\u003e531 (24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (3.3)\u003c/p\u003e \u003cp\u003e30 (7.1)\u003c/p\u003e \u003cp\u003e103 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (14.3)\u003c/p\u003e \u003cp\u003e73 (17.4)\u003c/p\u003e \u003cp\u003e360 (16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27 (29.7)\u003c/p\u003e \u003cp\u003e139 (33.1)\u003c/p\u003e \u003cp\u003e1193 (54.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCigarette smoking\u003c/p\u003e \u003cp\u003eNever smoked\u003c/p\u003e \u003cp\u003eEx-smoker\u003c/p\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e691 (28.4)\u003c/p\u003e \u003cp\u003e42 (26.8)\u003c/p\u003e \u003cp\u003e24 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120 (4.9)\u003c/p\u003e \u003cp\u003e9 (5.7)\u003c/p\u003e \u003cp\u003e7 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e405 (16.6)\u003c/p\u003e \u003cp\u003e24 (15.3)\u003c/p\u003e \u003cp\u003e17 (15.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1218 (50.0)\u003c/p\u003e \u003cp\u003e82 (52.2)\u003c/p\u003e \u003cp\u003e59 (55.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.819\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBad event occurring in the past month\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e315 (20.6)\u003c/p\u003e \u003cp\u003e442 (37.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 (5.4)\u003c/p\u003e \u003cp\u003e53 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e268 (17.5)\u003c/p\u003e \u003cp\u003e178 (15.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e864 (56.5)\u003c/p\u003e \u003cp\u003e495 (42.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e757 (28.1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e136 (5.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e446 (16.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1359 (50.4)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMore than half of the participants aged 35-100-years had severe to extremely severe stress (55.0%), more than half of the females had severe to extremely severe stress (52.6%), and almost one-third of the widowed/divorced participants had severe to extremely severe stress (62.0%). Less than half of the participants living in rural areas had severe to extremely stress (44.3%), and more than one-quarter of the participants who had low economic status had no stress (29.6%). There was a significant relationship between presence of severe/extremely severe stress and (i) age (more prevalent among older participants), (ii) gender (more prevalent among females), (iii) marital status (more prevalent among married and widow/divorced participants) (iv) residency (more prevalent among residents living in rural areas), (v) education (more prevalent among illiterate participants), (vi) economic status (more prevalent among participants with low income economic status), and (vii) bad events (more prevalent among participants who experienced a bad event during the past month [Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation of stress with participants socio-demographic characteristics (n\u0026thinsp;=\u0026thinsp;2698)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eStress\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMild\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEx/Severe\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003cp\u003e15\u0026ndash;34-years\u003c/p\u003e \u003cp\u003e35\u0026ndash;100-years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e737 (38.3)\u003c/p\u003e \u003cp\u003e167 (21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e197 (10.2)\u003c/p\u003e \u003cp\u003e43 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e295 (15.3)\u003c/p\u003e \u003cp\u003e138 (17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e695 (36.1)\u003c/p\u003e \u003cp\u003e426 (55.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003cp\u003eMale\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e545 (44.2)\u003c/p\u003e \u003cp\u003e359 (24.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125 (10.1)\u003c/p\u003e \u003cp\u003e115 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e213 (17.3)\u003c/p\u003e \u003cp\u003e220 (15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e351 (28.4)\u003c/p\u003e \u003cp\u003e770 (52.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003cp\u003eSingle\u003c/p\u003e \u003cp\u003eMarried\u003c/p\u003e \u003cp\u003eWidow/divorced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e399 (43.9)\u003c/p\u003e \u003cp\u003e488 (28.4)\u003c/p\u003e \u003cp\u003e17 (23.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108 (11.9)\u003c/p\u003e \u003cp\u003e129 (7.5)\u003c/p\u003e \u003cp\u003e3 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e152 (16.7)\u003c/p\u003e \u003cp\u003e274 (15.9)\u003c/p\u003e \u003cp\u003e7 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e250 (27.5)\u003c/p\u003e \u003cp\u003e827 (48.1)\u003c/p\u003e \u003cp\u003e44 (62.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidency\u003c/p\u003e \u003cp\u003eUrban\u003c/p\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e641 (35.7)\u003c/p\u003e \u003cp\u003e263 (29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180 (10.0)\u003c/p\u003e \u003cp\u003e60 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e255 (14.2)\u003c/p\u003e \u003cp\u003e178 (19.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e722 (40.2)\u003c/p\u003e \u003cp\u003e399 (44.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003cp\u003ePrimary school\u003c/p\u003e \u003cp\u003eSecondary school\u003c/p\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e168 (17.9)\u003c/p\u003e \u003cp\u003e103 (31.6)\u003c/p\u003e \u003cp\u003e167 (35.5)\u003c/p\u003e \u003cp\u003e281 (47.8)\u003c/p\u003e \u003cp\u003e185 (49.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (5.6)\u003c/p\u003e \u003cp\u003e27 (8.3)\u003c/p\u003e \u003cp\u003e37 (8.3)\u003c/p\u003e \u003cp\u003e37 (7.9)\u003c/p\u003e \u003cp\u003e71 (12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144 (15.4)\u003c/p\u003e \u003cp\u003e63 (19.3)\u003c/p\u003e \u003cp\u003e82 (17.4)\u003c/p\u003e \u003cp\u003e86 (14.6)\u003c/p\u003e \u003cp\u003e58 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e572 (61.1)\u003c/p\u003e \u003cp\u003e133 (40.8)\u003c/p\u003e \u003cp\u003e185 (39.3)\u003c/p\u003e \u003cp\u003e150 (25.5)\u003c/p\u003e \u003cp\u003e81 (21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEconomic status\u003c/p\u003e \u003cp\u003eHigh income\u003c/p\u003e \u003cp\u003eMiddle income\u003c/p\u003e \u003cp\u003eLow income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (63.7)\u003c/p\u003e \u003cp\u003e199 (47.4)\u003c/p\u003e \u003cp\u003e647 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (8.8)\u003c/p\u003e \u003cp\u003e50 (11.9)\u003c/p\u003e \u003cp\u003e182 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (8.8)\u003c/p\u003e \u003cp\u003e73 (17.4)\u003c/p\u003e \u003cp\u003e352 (16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17 (18.7)\u003c/p\u003e \u003cp\u003e98 (23.3)\u003c/p\u003e \u003cp\u003e1006 (46.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCigarette smoking\u003c/p\u003e \u003cp\u003eNever smoked\u003c/p\u003e \u003cp\u003eEx-smoker\u003c/p\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e822 (33.8)\u003c/p\u003e \u003cp\u003e51 (32.5)\u003c/p\u003e \u003cp\u003e31 (29.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e210 (8.6)\u003c/p\u003e \u003cp\u003e19 (12.1)\u003c/p\u003e \u003cp\u003e11 (10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e368 (15.1)\u003c/p\u003e \u003cp\u003e41 (26.1)\u003c/p\u003e \u003cp\u003e24 (22.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1034 (42.5)\u003c/p\u003e \u003cp\u003e46 (29.3)\u003c/p\u003e \u003cp\u003e41 (38.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBad event occurring in the past month\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e396 (25.9)\u003c/p\u003e \u003cp\u003e508 (43.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131 (8.6)\u003c/p\u003e \u003cp\u003e109 (9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e253 (16.5)\u003c/p\u003e \u003cp\u003e180 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e750 (49.0)\u003c/p\u003e \u003cp\u003e371 (31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e904 (33.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e240 (8.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e433 (16.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1121 (41.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eMultiple logistic regression analysis was performed to see which variables predicted depression, anxiety, and stress. The variables that were significantly associated with depression were: gender (being female) (AOR\u0026thinsp;=\u0026thinsp;1.746, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), economic status (having a low income) (AOR\u0026thinsp;=\u0026thinsp;2.627, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), residency (living in a rural area) (AOR\u0026thinsp;=\u0026thinsp;1.233, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043), education (being university level) (AOR\u0026thinsp;=\u0026thinsp;0.345, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), cigarette smoking (current-smoker) (AOR\u0026thinsp;=\u0026thinsp;2.785, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and a bad event occurring in the past month (AOR\u0026thinsp;=\u0026thinsp;0.436, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The variables that were significantly associated with anxiety were: age (being older) (AOR\u0026thinsp;=\u0026thinsp;1.526, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), gender (being female) (AOR\u0026thinsp;=\u0026thinsp;1.716, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), economic status (having a low income) (AOR\u0026thinsp;=\u0026thinsp;2.080, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002), residency (living in a rural area) (AOR\u0026thinsp;=\u0026thinsp;1.262, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.029), education (being university level) (AOR\u0026thinsp;=\u0026thinsp;0.237, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), cigarette smoking (current-smoker) (AOR\u0026thinsp;=\u0026thinsp;2.496, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and a bad event occurring in the past month (AOR\u0026thinsp;=\u0026thinsp;0.416, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The variables that were significantly associated with stress were: gender (being female) (AOR\u0026thinsp;=\u0026thinsp;2.353, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), economic status (having a low income) (AOR\u0026thinsp;=\u0026thinsp;2.747, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), education (being university level) (AOR\u0026thinsp;=\u0026thinsp;0.265, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), cigarette smoking (current smoker) (AOR\u0026thinsp;=\u0026thinsp;2.521, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and a bad event occurring in the past month (AOR\u0026thinsp;=\u0026thinsp;0.449, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). \u003cb\u003e[\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e]\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple logistic regression analysis of depression, anxiety and stress on participants\u0026rsquo; sociodemographic characteristics in Afghanistan (n\u0026thinsp;=\u0026thinsp;2698)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStress\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAOR [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAOR [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAOR [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep-\u003c/em\u003evalue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;34-years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;100-years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.211 [0.950, 1.543]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.526 [1.182, 1.972]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.250 [0.990, 1.578]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.061\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.762 [1.463, 2.123]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.716 [1.419, 2.074]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.353 [1.963, 2.820]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEconomic status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.586 [1.257, 2.002]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.618 [1.279, 2.047]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.613 [1.281, 2.031]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.627 [1.669, 4.136]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.080 [1.315, 3.292]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.747 [1.717, 4.395]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidency\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.233 [1.007, 1.511]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e.043\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.262 [1.025, 1.554]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e.029\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.042 [0.858, 1.265]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.678\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.913 [0.691, 1.205]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.904 [0.686, 1.190]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.923 [0.701, 1.215]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.568\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.593 [0.438, 0.802]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.524 [0.388, 0.708]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.577 [0.430, 0.775]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.466 [0.330, 0.659]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.403 [0.285, 0.570]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.488 [0.351, 0.679]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.345 [0.254, 0.469]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.237 [0.173, 0.324]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.265 [0.196, 0.358]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCigarette smoking\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever smoked\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEx-smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.724 [0.919, 3.237]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.790 [0.970, 3.304]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.632 [0.923, 2.885]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.092\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.785 [1.663, 4.666]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.496 [1.514, 4.115]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.521 [1.589, 3.999]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTraumatic event\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.436 [0.364, 0.523]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.412 [0.343, 0.496]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.449 [0.376, 0.536]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe mental health of Afghans living under Taliban rule is a matter of the utmost importance, and it is essential to understand some of the complex factors contributing to this issue. The Taliban's return to power in Afghanistan has brought about significant political, social, and economic changes that appear to have had a profound impact on the well-being of the Afghan population [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Several studies have reported severe anxiety, depression and stress among the Afghan people but these have been localized studies and/or included a specific proportion of the Afghan society [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The present national survey was carried out to examine the mental health issues faced by Afghan people and determine the socio-demographic factors associated stress, anxiety, and depression. In the present study, less than one-fifth of the participants (18.9%) did not exhibit any signs of depression, anxiety, or stress.\u003c/p\u003e \u003cp\u003eIn the present study, approximately one-fifth of the participants (27.9%) indicated a mental state free of any depression symptoms, with females exhibiting a higher prevalence of depressive symptoms (77.6%) than males (65.5%). Consistent with previous research, gender emerged as a significant factor influencing mental health status, with females manifesting elevated levels of mental health disorders compared to males [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The findings indicated that 64.5% of those reporting depression symptoms also reported anxiety symptoms. Moreover, 62.0% of individuals reporting depressive symptoms also reported experiencing stress. Factors significantly associated with depression included age (being older), gender (being female), marital status (being widow/divorced), residency (residing in rural areas), education level (having lower educational attainment), economic status (having a low monthly income), cigarette smoking (being a current smoker), and experiencing a bad event in the past month.\u003c/p\u003e \u003cp\u003eThe prevalence of depressive symptoms in the present study is much higher than the reported range by the World Health Organization (WHO), which indicates a frequency of 1 in 10 individuals in areas affected by conflict. However, the present study found a markedly elevated prevalence of nearly 7 in 10 individuals, greatly surpassing the figures by the WHO [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Those aged over 34 years, exhibited a much higher prevalence of depressive symptoms (81.1%) compared to the younger age group aged under 35 years (68.4%). In comparison, data from a 2019 interview survey conducted by the Centers for Disease Control and Prevention (CDC) in the US indicated that 21.0% of adults aged 18\u0026ndash;29 years experienced depressive symptoms, compared to 16.8% among adults aged 30\u0026ndash;44 years [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe disparity in depressive symptoms between age groups may reflect differences in life stressors, financial burdens, and social isolation, with older individuals potentially facing more complex challenges. The findings of this study align with a previous study which reported 79.0% depression among women in Afghanistan (79.0%) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This suggests that depression symptoms remained the same even after the war ended in Afghanistan. This finding is consistent with another study which found that psychological distress symptoms were prevalent among 75% of the national Afghan population [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], but much higher than a study among Afghan pregnant women which reported the prevalence of depression to be 60.9% [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], Compared to countries elsewhere in the world, a systematic review by Mahmud et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] examining depression during COVID-19 indicated that 30.5% of the global population exhibited symptoms of depression. These findings suggest that in Afghanistan, the prevalence of depression exceeds that of the global average. Notably, under the Taliban government, there has been a slight increase in this prevalence.\u003c/p\u003e \u003cp\u003eMoreover, in the present study, the presence of depressive symptoms was significantly associated with educational attainment, with illiterate participants reporting a higher prevalence (83.2%) compared to those with a university education (58.6%). This is in line with findings of previous study in Afghanistan that reported a significant association between educational level and presence of depression symptoms [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This finding also aligns with a European study that reported higher levels of education being associated with lower odds of depression [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. A meta-analysis further supports the crucial role of educational levels in shaping mental health outcomes, including depression, showing that those with lower education have poorer mental health outcomes [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlmost three-quarters of participants reported anxiety symptoms (71.9%) with those aged over 34 years reporting a higher prevalence (84.9%), in contrast to those aged under 35 years (66.7%). This is in line with findings of a previous study among women in Afghanistan (n\u0026thinsp;=\u0026thinsp;438) which reported that the prevalence of anxiety among older participants (75.6%) was higher than younger ones (89.1%) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], a finding that is generally supported in the literature [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This differs from findings in a study conducted in Iran (n\u0026thinsp;=\u0026thinsp;7886), where the prevalence of anxiety was reported to be higher among younger participants (20.1%) than older participants (13.8%) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Additionally, a study conducted in Malaysia (n\u0026thinsp;=\u0026thinsp;506) reported higher levels of anxiety in the younger age group (9.61%) compared to old age groups (12.8%) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. A meta-analysis by Mahmud et al. reported that 29.6% of the world population during the COVID-19 pandemic had anxiety [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This suggests that compared to the rest of the world, anxiety appears to be more prevalent in Afghanistan. The different rate observed in the present study\u0026rsquo;s findings compared to other studies may be due to cultural, geographic, and methodological differences, impacting the manifestation and disclosure of anxiety symptoms across distinct demographic cohorts and locales.\u003c/p\u003e \u003cp\u003eMarital status emerged as another significant factor associated with anxiety symptoms, with widowed/divorced participants reporting the highest percentage of anxiety (85.9%) compared to the other two groups (61.3% single and 77.0% married). This aligns with prior systematic reviews indicating that being divorced or widowed are significant predictors of anxiety among women [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. This is in line with previous study in Afghanistan (n\u0026thinsp;=\u0026thinsp;438) which reported higher prevalence of anxiety among divorced participants compared to single and married participants [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWith regards to educational attainment, participants with at least a university-level education reported the lowest levels of anxiety (55.2%), while a significantly higher proportion of illiterate participants reported anxiety symptoms (87.0%). This observation aligns with a previous study in India (n\u0026thinsp;=\u0026thinsp;180) indicating an increased likelihood of anxiety among women with lower educational attainment [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Moreover, in the present study, specific demographic subgroups reported elevated anxiety levels compared to their counterparts. More specifically, those with a low family monthly income recorded a higher prevalence of anxiety (75.7%) in comparison to those with a high family monthly income (47.3%). This finding is in line with the findings of a previous study in Afghanistan (n\u0026thinsp;=\u0026thinsp;664) that reported higher prevalence of anxiety among low monthly family income participants compared to high income monthly family income [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Additionally, individuals who experienced a negative event in the past month reported higher anxiety levels (79.4%) compared to those who did not (62.2%). These findings align with the findings of previous aforementioned study in Afghanistan that reported higher prevalence of anxiety among participants who experienced negative event in the past month than those who had not [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOver half of participants aged over 34 years (55%) reported symptoms of stress. The study found significant associations between various demographic factors and stress, including gender, age group, marital status, residency, traumatic experiences, and economic status. More specifically, the findings indicated that older individuals, females, and those with lower income levels reported more stress than their counterparts. These findings are novel as no previous study in Afghanistan has assessed the prevalence of stress among the general population. However, studies have been conducted on the mental health of healthcare workers [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], adolescents [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], and women in Afghanistan [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. These results diverge from those of a systematic review conducted by Salari et al. among general population [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], which identified a negative association between stress and the age group of participants (n\u0026thinsp;=\u0026thinsp;9074).\u003c/p\u003e \u003cp\u003eIn the present study, prevalence of stress was found at 66.49%. This is much higher than the findings of two systematic reviews by Mahmud et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and Salari et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] who reported that during the COVID-19 pandemic, the prevalence of stress was 29.4% and 29.6% globally, respectively [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In the present study, a higher prevalence of stress was observed among married participants (71.6%) compared to their single counterparts (56.1%). This contrasts with findings in a study by Cao et al. in China [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], where prevalence of stress among single marital status was higher than married participants (n\u0026thinsp;=\u0026thinsp;9030). Moreover, the impact of traumatic experiences on individuals' lives cannot be understated [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], and the findings of the present study reinforce existing evidence that individuals with a history of traumatic events are more susceptible to the development of stress [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. These findings underscore the intricate interplay between demographic variables, life experiences, and stress manifestation, contributing valuable insights to the understanding of stress dynamics within diverse populations.\u003c/p\u003e \u003cp\u003eMultiple regression analysis indicated that gender (being female), economic status (being poor), residency (living in rural areas), education level (being illiterate), being a cigarette smoker, and having experienced a traumatic event during the past month were significantly associated with depression, anxiety and stress. These findings underscore the interplay of these demographic and behavioral factors in influencing the manifestation of mental health symptoms. Importantly, extant literature has consistently corroborated the significant impact of depression on these specific demographic factors, as evidenced by prior studies [\u003cspan additionalcitationids=\"CR47 CR48 CR49\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], further affirming the robustness of the present study\u0026rsquo;s findings. The study\u0026rsquo;s findings also indicate the multifaceted nature of the possible determinants of anxiety symptoms, providing insight into the interconnectedness of various demographic and behavioral elements. Notably, existing research has consistently highlighted the substantial impact of anxiety on the aforementioned demographic factors, as substantiated by a body of literature spanning prior investigations [\u003cspan additionalcitationids=\"CR52 CR53 CR54 CR55 CR56\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA significant proportion of cigarette smokers in the present study (80.4%) exhibited indications of depressive symptoms. Additionally, 77.6% of current smokers displayed symptoms indicative of anxiety, while 71.0% reported experiencing symptoms associated with stress. Current smokers exhibited a prevalence of depressive symptoms 2.8 times greater than individuals who had never smoked. Similarly, they displayed a prevalence of anxiety symptoms 2.5 times higher and a prevalence of stress symptoms 2.5 times higher compared to individuals who had never smoked. These findings are in line with results of a systematic review conducted by Fluharty et al. which reported that smoking was associated with depression and anxiety [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Other systematic reviews have reported that smoking is associated with depression [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] and anxiety [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], and that the relationships are bi-directional, and that one can lead to another [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is noteworthy that the present study\u0026rsquo;s findings resonate with broader trends observed in the national Afghan landscape. A study conducted in major provinces of Afghanistan in 2021 (n\u0026thinsp;=\u0026thinsp;664) reported that almost four-fifths of Afghan women exhibited depression symptoms (79.1%) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. This alignment of findings suggests an increase in high prevalence of mental health disorders among the Afghan population.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eThe present study had a number of limitations. Firstly, the study lacked an assessment of the onset dates of depression, anxiety, and/or stress, precluding the determination of whether participants' mental health conditions changed post-Taliban takeover or had pre-existing origins. Notably, the reliance on self-reported data introduces potential methodological biases, despite providing estimates of depression, anxiety, and stress among the Afghan population and their associations with socio-demographic factors. The cross-sectional design of the study further restricts the capacity to determine causality between the examined variables. Furthermore, the non-representative nature of the sample is a limitation because it encompasses participants from only three regions in Afghanistan, with an overrepresentation of urban residents compared to the national distribution. Consequently, the sample exhibits a disproportionately lower proportion of illiterate participants than the national demographic composition, undermining the generalizability of the study's findings to all Afghans. The scarcity of previous investigations into the mental health of the general Afghan population since the resurgence of the Taliban hindered the ability to contextualize and compare the results of the present study with other studies, limiting the discernment of meaningful trends.\u003c/p\u003e"},{"header":"Conclusion and recommendations","content":"\u003cp\u003eThe mental health crisis in Afghanistan is a complex and urgent issue that requires a comprehensive and compassionate response. The findings of the present study showed very high levels of anxiety, depression, and stress among the participants. The study offered important insights into the mental health status of Afghans living under the Taliban government. The high prevalence rates of depression, anxiety, and stress underscore the substantial psychological burden experienced by the population. The identified socio-demographic factors, such as being female, being of low economic status, living in rural regions, having a low education level, being a cigarette smoker, and recent traumatic experiences, highlight the complexity of mental health disparities in this context. These findings emphasize the pressing need for targeted and culturally sensitive interventions to address the multifaceted challenges contributing to the high prevalence of mental health disorders. Tailored mental health programs, informed by the findings here, could play a pivotal role in mitigating the impact of psychological distress and promoting overall well-being among Afghans living under the current sociopolitical circumstances.\u003c/p\u003e \u003cp\u003eThe findings of the present study suggest a potential comorbidity between mental health disorders and various socio-demographic vulnerabilities among Afghans, necessitating urgent attention to address the prevailing mental health challenges under the current Taliban governance. Subsequent research endeavors should explore the origins of therapeutic resources and assess their accessibility within the broader Afghan population. Moreover, as the international community engages with Afghanistan, it must prioritize the well-being of the Afghan individuals and provide the necessary resources to address their mental health needs. This includes providing funding for mental health services, training local mental health professionals, and raising awareness about mental health issues to reduce stigma.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConsent for publication\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthical considerations\u003c/h2\u003e \u003cp\u003e The Afghanistan Center for Epidemiological Studies \u0026ndash; Ethical Committee granted ethical clearance for the implementation of this study (reference number #23.1.039). Subsequent to initial engagement with participants, a comprehensive overview of the study was provided. Consent, whether written or verbal, was procured from all participants involved in the study. For participants under the age of 18, consent was obtained from their parents. Participants were duly informed of their right to withdraw from the study at any juncture. All methodologies employed in this study adhere to the principles outlined in the Declaration of Helsinki.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eDeclaration of Interests:\u003c/h2\u003e \u003cp\u003eAuthors of this study declare that there is no competing interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis study did not receive external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAN and AQM designed the study. NR, BAR, SS, NRa, and ZT collected the data. AN, and PS analyzed the data. AN, AQM, NR, PS and BAR prepared the draft of the manuscript. AN, BAR and MG critically reviewed, rewrote, edited, and finalized the manuscript. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement:\u003c/h2\u003e \u003cp\u003eWe would like to express our sincere gratitude to all the participants who enrolled in this study.\u003c/p\u003e\u003ch2\u003eAvailability of data:\u003c/h2\u003e \u003cp\u003eAll data relevant to the study are included in the article or uploaded as supplementary information\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAfghanistan Country Profile [Internet]. BBC; 2023 [cited 2023 Dec 15]. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bbc.com/news/world-south-asia-12011352\u003c/span\u003e\u003cspan address=\"https://www.bbc.com/news/world-south-asia-12011352\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAfghanistan [Internet]. World Health Organization; 2021 [cited 2023 Dec 15]. 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Evidence from a systematic literature review and meta-analysis. European Psychiatry. 2015;30(6):756\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFluharty M, Taylor AE, Grabski M, Munaf\u0026ograve; MR. The association of cigarette smoking with depression and anxiety: a systematic review. Nicotine \u0026amp; Tobacco Research. 2016;19(1):3\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChaiton MO, Cohen JE, O'Loughlin J, Rehm J. A systematic review of longitudinal studies on the association between depression and smoking in adolescents. BMC Public Health. 2009;9:1\u0026ndash;1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarey L, Olofsson H, Garza T, Shepherd JM, Smit T, Zvolensky MJ. The role of anxiety in smoking onset, severity, and cessation-related outcomes: A review of recent literature. Current Psychiatry Reports. 2020;22:1\u0026ndash;0.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-mental-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dimh","sideBox":"Learn more about [Discover Mental Health](https://www.springer.com/44192)","snPcode":"","submissionUrl":"","title":"Discover Mental Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"depression, anxiety, stress, Afghanistan, Taliban","lastPublishedDoi":"10.21203/rs.3.rs-4149818/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4149818/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The present cross-sectional survey study examined the mental health of Afghans living under the Taliban government. It examined the underlying factors associated with depression, anxiety, and stress.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Between June 5, 2023 and February 12, 2024, a cross-sectional study was conducted among the Afghan population in three key regions of Afghanistan. Data were collected using a pretested structured questionnaire. Logistic regression models were employed to explore the relationship between socio-demographic characteristics and depression, anxiety, and stress among 2,698 participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The prevalence of (i) depression was 72.05%, (ii) anxiety was 71.94%, and (iii) stress was 66.49%. Multiple regression analysis indicated that gender (being female), economic status (being poor), residency (living in rural areas), education level (being illiterate), being a cigarette smoker, and having experienced a traumatic event during the past month were significantly associated with depression, anxiety and stress.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The mental health crisis in Afghanistan is a complex and urgent issue that requires a comprehensive and compassionate response. The findings of the present study show very high levels of anxiety, depression, and stress, most likely reflecting the profound impact of recent political, social, and economic changes. Notably, a significant majority of participants, particularly females and individuals above 35 years of age, reported severe to extremely severe mental health symptoms.\u003c/p\u003e","manuscriptTitle":"Health survey on anxiety, depression, and stress in Afghanistan: A large-scale cross-sectional survey study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-29 15:20:19","doi":"10.21203/rs.3.rs-4149818/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-02T06:48:37+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-28T01:50:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-16T12:11:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"fa77fa2c-6d80-4515-adc6-ca6f18155ea2_SNPRID","date":"2024-04-15T12:58:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"80efcf82-644a-4e6b-af38-32bf79eb3716","date":"2024-04-14T03:37:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-14T02:30:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-12T19:07:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-12T19:05:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Mental Health","date":"2024-03-22T12:38:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-mental-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dimh","sideBox":"Learn more about [Discover Mental Health](https://www.springer.com/44192)","snPcode":"","submissionUrl":"","title":"Discover Mental Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5b27e12a-24df-40c4-8f0d-efba1d76ad7e","owner":[],"postedDate":"April 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-08-28T15:01:23+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-29 15:20:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4149818","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4149818","identity":"rs-4149818","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}